docstr: Default replay buffer factory.
docstr_tok: ["Default","replay","buffer","factory","."]
code: def _make_replay_buffer(self, tf_env):
      """Default replay buffer factory."""
  
      time_step_spec = tf_env.time_step_spec()
      action_spec = tf_env.action_spec()
      action_step_spec = policy_step.PolicyStep(
          action_spec, (), tensor_spec.TensorSpec((), tf.int32)
      )
      trajectory_spec = trajectory.from_transition(
          time_step_spec, action_step_spec, time_step_spec
      )
      return episodic_replay_buffer.EpisodicReplayBuffer(
          trajectory_spec, end_episode_fn=lambda _: False
      )
  
file_path: agents/tf_agents/replay_buffers/episodic_replay_buffer_driver_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  from tf_agents.drivers import dynamic_episode_driver
  from tf_agents.drivers import test_utils
  from tf_agents.environments import batched_py_environment
  from tf_agents.environments import tf_py_environment
  from tf_agents.replay_buffers import episodic_replay_buffer
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.trajectories import trajectory
  from tf_agents.utils import test_utils
label_desc: Use image node_id 1 for calling the EpisodicReplayBufferDriverTest obj's underlying member method code with example usage: obj._make_replay_buffer(tf_env) and returns: episodic_replay_buffer